Abstract

Pose estimation of outdoor robots presents some distinct challenges due to
the various uncertainties in the robot sensing and action. In particular,
global positioning sensors of outdoor robots do not always work perfectly,
causing large drift in the location estimate of the robot. To overcome
this common problem, we propose a new approach for global localization
using place recognition. First, we learn the location of some arbitrary
key places using odometry measurements and GPS measurements only at the
start and the end of the robot trajectory. In subsequent runs, when the
robot perceives a key place, our fixed-lag smoother fuses odometry
measurements with the relative location to the key place to improve its
pose estimate. Outdoor mobile robot experiments show that place
recognition measurements significantly improve the estimate of the
smoother in the absence of GPS measurements.